Manager Master Data Integrity

Tyson Foods, Inc.•Springdale, AR

About The Position

The Manager, Master Data Integrity, owns the accuracy, consistency, and governance of Tyson’s Sales and Customer hierarchies. This includes customer account structures—sold-to, region, chain, and parent relationships—and sales organization and account-owner alignments across SAP, Trade Management, analytics platforms, and related systems. This role is the subject matter expert and accountable owner for these data domains. The Manager works with Sales, Finance, Customer Service, Master Data Governance, Demand Planning, and IT to prevent and resolve data issues and protect the order accuracy, trade spend, and reporting that depend on reliable data. The role also leads and develops a team, influences data standards across Commercial and IT, and represents hierarchy data requirements in system and process projects. Success includes documented standards and repeatable change processes; measured data quality with a target of 99% accuracy and fewer hierarchy-related errors, corrections, and rework; proactive assessment and communication of hierarchy changes; minimal downstream disruption; and trusted data among business partners.

Requirements

Bachelor’s degree in Business Administration, Information Technology, or a related analytical field, or equivalent experience.
5–7 years of experience in master data management, data governance, or data quality.
Experience leading, influencing, and mentoring team members, formally or informally.
Advanced proficiency in Excel.
Strong working knowledge of SAP systems, including customer master data and hierarchy structures.
Exceptional influencing skills and the ability to communicate effectively at all organizational levels.
Strong understanding of technology and data principles, with the ability to navigate complex systems.
Ability to manage data end to end, from creation and maintenance through downstream use in reporting and decision-making.
Detail-oriented, with the ability to assess broader implications of system or data changes.
Ability to challenge requests that would compromise data integrity and offer solution-oriented alternatives.
Intellectual curiosity and commitment to continuous improvement.
Willingness and ability to perform the physical requirements of the job, with or without reasonable accommodation.
As a people leader, ability to drive responsible AI adoption, enable effective use of approved solutions, identify opportunities to improve team performance through AI, and ensure accountability for AI-supported outcomes.

Nice To Haves

1–2 years of project or change management experience.
Familiarity with the Food Service, Retail, or Packaged Goods industries.
Experience with customer or sales master data in SAP.

Responsibilities

Serve as champion and subject matter expert for Sales and Customer hierarchy data, maintaining data interdependencies and quality across platforms.
Own the end-to-end process for creating, changing, and maintaining Sales and Customer hierarchies.
Lead commercial sales data quality management by defining and reporting metrics, identifying and resolving inconsistencies and gaps, and conducting root-cause analysis to prevent recurring issues.
Assess downstream effects of hierarchy changes—including customer reorganizations, new accounts, sales realignments, and acquisitions—on pricing, trade programs, invoicing, and reporting before implementation.
Collaborate with stakeholders across the organization to address cross-functional data requirements.
Partner with business users and IT to execute data changes in a controlled and well-communicated manner while maintaining data integrity.
Establish, document, and advocate for data quality standards, procedures, and governance practices, influencing stakeholders to adopt best practices.
Represent hierarchy data requirements in system and process projects, including implementations, upgrades, and organizational changes.
Lead, influence, and mentor team members, and drive responsible adoption of approved AI solutions as a people leader.
Assess and communicate hierarchy changes before implementation to minimize downstream disruption.
Measure and report data quality, targeting 99% accuracy and reductions in errors, corrections, and rework.